Main Memory Evaluation of Monitoring Queries Over Moving Objects

  • Authors:
  • Dmitri V. Kalashnikov;Sunil Prabhakar;Susanne E. Hambrusch

  • Affiliations:
  • Department of Computer Sciences, Purdue University, West Lafayette, Indiana 47907, USA. dvk@cs.purdue.edu;Department of Computer Sciences, Purdue University, West Lafayette, Indiana 47907, USA. sunil@cs.purdue.edu;Department of Computer Sciences, Purdue University, West Lafayette, Indiana 47907, USA. seh@cs.purdue.edu

  • Venue:
  • Distributed and Parallel Databases
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we evaluate several in-memory algorithms for efficient and scalable processing of continuous range queries over collections of moving objects. Constant updates to the index are avoided by query indexing. No constraints are imposed on the speed or path of moving objects or fraction of objects that move at any moment in time. We present a detailed analysis of a grid approach which shows the best results for both skewed and uniform data. A sorting based optimization is developed for significantly improving the cache hit-rate. Experimental evaluation establishes that indexing queries using the grid index yields orders of magnitude better performance than other index structures such as R*-trees.